Summary of 2_DecisionTree
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Decision Tree
- n_jobs: -1
- criterion: gini
- max_depth: 3
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
- stratify: True
Optimized metric
logloss
Training time
12.9 seconds
Metric details
|
score |
threshold |
| logloss |
0.745252 |
nan |
| auc |
0.589583 |
nan |
| f1 |
0.580645 |
0.264344 |
| accuracy |
0.625 |
0.643939 |
| precision |
0.466667 |
0.454545 |
| recall |
1 |
0.0321429 |
| mcc |
0.258199 |
0.264344 |
Metric details with threshold from accuracy metric
|
score |
threshold |
| logloss |
0.745252 |
nan |
| auc |
0.589583 |
nan |
| f1 |
0.222222 |
0.643939 |
| accuracy |
0.625 |
0.643939 |
| precision |
0.428571 |
0.643939 |
| recall |
0.15 |
0.643939 |
| mcc |
0.0563436 |
0.643939 |
Confusion matrix (at threshold=0.643939)
|
Predicted as 0 |
Predicted as 1 |
| Labeled as 0 |
32 |
4 |
| Labeled as 1 |
17 |
3 |
Learning curves

Decision Tree
Tree #1
Rules
if (time <= 198.5) and (platelets <= 267500.0) and (creatinine_phosphokinase > 118.0) then class: 0 (proba: 72.13%) | based on 61 samples
if (time <= 198.5) and (platelets > 267500.0) and (time > 60.5) then class: 0 (proba: 54.55%) | based on 33 samples
if (time > 198.5) and (platelets <= 399500.0) and (age > 50.5) then class: 0 (proba: 96.43%) | based on 28 samples
if (time <= 198.5) and (platelets <= 267500.0) and (creatinine_phosphokinase <= 118.0) then class: 1 (proba: 55.0%) | based on 20 samples
if (time <= 198.5) and (platelets > 267500.0) and (time <= 60.5) then class: 1 (proba: 83.33%) | based on 12 samples
if (time > 198.5) and (platelets <= 399500.0) and (age <= 50.5) then class: 0 (proba: 75.0%) | based on 8 samples
if (time > 198.5) and (platelets > 399500.0) and (platelets > 436500.0) then class: 0 (proba: 100.0%) | based on 3 samples
if (time > 198.5) and (platelets > 399500.0) and (platelets <= 436500.0) then class: 1 (proba: 100.0%) | based on 3 samples
Permutation-based Importance

Confusion Matrix

Normalized Confusion Matrix

ROC Curve

Kolmogorov-Smirnov Statistic

Precision-Recall Curve

Calibration Curve

Cumulative Gains Curve

Lift Curve

SHAP Importance

SHAP Dependence plots
Dependence (Fold 1)

SHAP Decision plots
Top-10 Worst decisions for class 0 (Fold 1)

Top-10 Best decisions for class 0 (Fold 1)

Top-10 Worst decisions for class 1 (Fold 1)

Top-10 Best decisions for class 1 (Fold 1)

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